AFM Imaging of Immobilized Fibronectin: Does the Surface Conjugation Scheme Affect the Protein Orientation/Conformation?
Bibliographic record
Abstract
Covalent grafting of biomolecules could potentially improve the biocompatibility of materials. However, these molecules have to be grafted in an active conformation to play their biological roles. The present work aims at verifying if the surface conjugation scheme of fibronectin (FN) affects the protein orientation/conformation and activity. FN was grafted onto plasma-treated fused silica using two different crosslinkers, glutaric anhydride (GA) or sulfosuccinimidyl 4-(p-maleimidophenyl)butyrate (SMPB). Fused silica was chosen as a model surface material because it presents a roughness well below the dimensions of FN, therefore allowing AFM analyses with appropriate depth resolution. Cell adhesion assays were performed to evaluate the bioactivity of grafted FN. Cell adhesion was found to be higher on GA-FN than on SMPB-FN. Since FN-radiolabeling assays allowed us to rule out a surface concentration effect (approximately 80 ng/cm2 of FN on both crosslinkers), it was hypothesized that FN adopted a more active conformation when grafted via GA. In this context, the FN conformation on both crosslinkers was investigated through AFM and contact angle analyses. Before FN grafting, GA- and SMPB-modified surfaces had a similar water contact angle, topography, and roughness. However, water contact angles of GA-FN and SMPB-FN surfaces clearly show differences in surface hydrophilicity, therefore indicating a dependence of protein organization toward the conjugation strategy. Furthermore, AFM results demonstrated that surface topography and roughness of both FN-conjugated surfaces were significantly different. Distribution analysis of FN height and diameter confirmed this observation as the protein dimensions were significantly larger on GA than SMPB. This study confirmed that the covalent immobilization scheme of biomolecules influences their conformation and, hence, their activity. Consequently, selecting the appropriate conjugation strategy is of paramount importance in retaining molecule bioactivity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".